AI SEO alt text generator

lib/ai_seo_tools/image_alt_text_generator.py

@@ -0,0 +1,77 @@
+import streamlit as st
+import base64
+import requests
+from PIL import Image
+import os
+
+
+# Function to encode the image
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+def get_image_description(image_path):
+    base64_image = encode_image(image_path)
+
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"
+    }
+
+    payload = {
+        "model": "gpt-4o-mini",
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": """You are an SEO expert specializing in writing optimized Alt text for images. 
+            Your goal is to create clear, descriptive, and concise Alt text that accurately represents 
+            the content and context of the given image. Make sure your response is optimized for search engines and accessibility."""
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{base64_image}"
+                        }
+                    }
+                ]
+            }
+        ],
+        "max_tokens": 300
+    }
+
+    response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+    response_data = response.json()
+
+    # Extract the content field from the response
+    content = response_data['choices'][0]['message']['content']
+    return content
+
+
+def alt_text_gen():
+    st.title("Image Description Generator")
+
+    image_path = st.text_input("Enter the full path of the image file")
+
+    if image_path:
+        if os.path.exists(image_path) and image_path.lower().endswith(('jpg', 'jpeg', 'png')):
+            try:
+                image = Image.open(image_path)
+                st.image(image, caption='Uploaded Image', use_column_width=True)
+
+                if st.button("Get Image Alt Text"):
+                    with st.spinner("Generating Alt Text..."):
+                        try:
+                            description = get_image_description(image_path)
+                            st.success("Alt Text generated successfully!")
+                            st.write("ALt Text:", description)
+                        except Exception as e:
+                            st.error(f"Error generating description: {e}")
+            except Exception as e:
+                st.error(f"Error processing image: {e}")
+        else:
+            st.error("Please enter a valid image file path ending with .jpg, .jpeg, or .png")
+    else:
+        st.info("Please enter the full path of an image file.")

lib/ai_seo_tools/plagiarism_checker_from_known_sources.py

@@ -1,80 +0,0 @@
-import re
-
-#######################################################################
-#
-# I want you to act as a plagiarism checker. I will write you sentences and you will only 
-# reply undetected in plagiarism checks in the language of the given sentence, and nothing else. 
-# Do not write explanations on replies. My first sentence is {}
-#
-######################################################################
-
-
-class PlagiarismChecker:
-    def __init__(self, known_sources):
-        self.known_sources = known_sources
-
-    def check_plagiarism(self, html_content):
-        try:
-            # Preprocess the HTML content by removing HTML tags and extra spaces
-            text = re.sub(r'<[^>]+>', ' ', html_content)
-            text = re.sub(r'\s+', ' ', text).strip().lower()
-
-            # Check for exact matches with known sources
-            for source in self.known_sources:
-                source_text = re.sub(r'<[^>]+>', ' ', source)
-                source_text = re.sub(r'\s+', ' ', source_text).strip().lower()
-                if text == source_text:
-                    return f"Plagiarism detected: Matches known source - {source}"
-
-            # If no exact matches are found
-            return "No plagiarism detected. Content is original."
-
-        except Exception as e:
-            return str(e)
-
-# Example usage:
-if __name__ == "__main__":
-    # List of known sources
-    known_sources = [
-        """
-        <html>
-        <head>
-            <title>Sample Page 1</title>
-        </head>
-        <body>
-            <h1>Hello, World!</h1>
-            <p>This is sample content from known source 1.</p>
-        </body>
-        </html>
-        """,
-        """
-        <html>
-        <head>
-            <title>Sample Page 2</title>
-        </head>
-        <body>
-            <h1>Welcome to Known Source 2</h1>
-            <p>This is some content from another known source.</p>
-        </body>
-        </html>
-        """
-    ]
-
-    # HTML content to check for plagiarism
-    html_content = """
-    <html>
-    <head>
-        <title>Sample Page</title>
-    </head>
-    <body>
-        <h1>Hello, World!</h1>
-        <p>This is sample content.</p>
-    </body>
-    </html>
-    """
-
-    plagiarism_checker = PlagiarismChecker(known_sources)
-    result = plagiarism_checker.check_plagiarism(html_content)
-
-    print(result)
-